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Data-Centric Storage in Sensornets Submitted to Sigcomm 2002

Data-Centric Storage in Sensornets Submitted to Sigcomm 2002. Authors: Sylvia Ratnasamy et al. ICIR, UCLA, UC-Berkeley Presenter: Shang-Chieh Wu (meou@cs). Sensornets.

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Data-Centric Storage in Sensornets Submitted to Sigcomm 2002

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  1. Data-Centric Storage in SensornetsSubmitted to Sigcomm 2002 Authors: Sylvia Ratnasamy et al. ICIR, UCLA, UC-Berkeley Presenter: Shang-Chieh Wu (meou@cs)

  2. Sensornets • Sensornets are large-scale distributed sensing networks comprised of many small sensing devices equipped with memory, processors, and short-range radio • Monitor temperature in an active volcano, keep track of the seismic waves in an earthquake region, or even save rare and endangered species.

  3. Sensornets • Scalable, self-organizing and energy-efficient data dissemination algorithm required. • Data-centric routing algorithm. • Data-centric storage.

  4. Terminology • Observations: The low-level output from the sensors. • Events: Certain constellations of low-level observations. • Task: The code running on each sensor. • Query: Elicit the event information from the sensornet.

  5. External, Local, and Data-Centric Storage • External Storage(ES): On detection of events, the relevant data is sent to external storage. • Local Storage (LS): Event information is stored locally. • Data-Centric Storage (DS): After an event is detected, the data is stored by name within the sensornets.

  6. ES, LS, DS • Assume n nodes totally and the diameter of the sensornet is O(n0.5) Communication Costs per each

  7. ES, LS, DS • Dtotal : The total number of events detected. • Q: the number of event types for which queries are issued. • Dq: the number of events detected for the types of events queried for. • No more than one query for each event type, so there are Q queries in total. • Assume hotspot occurs on packets sending to the access point.

  8. ES, LS, DS Approximate Communication Costs • DS is preferable in • Sensornet is large • Dtotal >> max[Q + Dq] (??) • Summarises are used.

  9. Data-centric storage • Based • GPSR geographic routing algorithm. • Efficient peer-to-peer lookups system. • Relevant data is stored, by name, at nodes within the sensornet. All data with the same general name will be stored at the same sensornet node. • As an alternative method.

  10. GPSR • Strongly geographic routing algorithm. • Each mode determines its own geographic coordinates and periodically announces its address and coordinates to its neighbors. • Each mode is aware of the identifications and positions of all its neighbors. • Special rule to handle dead-ends.

  11. GPSR

  12. GPSR Right-hand rule: Each node to receive a packet forwards the packet on the next link counterclockwise about itself from the ingress link.

  13. Distributed Hash-Table • Given an event name, we hash the name into a key. The key is a location somewhere in the sensornets. • Put(key, value) command sends a packet with the given payload into the sensornet routed towards the location key. • MIT’s GLS is a good candidate. • Some extra concepts are proposed to handle failure, mobility, and scalability.

  14. Conclusion • Storages are involved in sensornets, another option. • A detail evaluation for transmission cost from collecting data to answering queries.

  15. My opinions • Database approaches for sensornets. • No serious contribution in real key issue.(routing and hashing) • Oversimplify the difficulty of “summary events”. • Lengthy introduction for sensornet. • The cost of failure for storages is neglected, On purpose ? • Data consistence in storages ?

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